6,992 research outputs found

    Distributed Fault-Tolerant Consensus Tracking Control of Multi-Agent Systems under Fixed and Switching Topologies

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    This paper proposes a novel distributed fault-tolerant consensus tracking control design for multi-agent systems with abrupt and incipient actuator faults under fixed and switching topologies. The fault and state information of each individual agent is estimated by merging unknown input observer in the decentralized fault estimation hierarchy. Then, two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation. Simulation results demonstrate the effectiveness of the proposed fault-tolerant consensus tracking control algorithm

    Defense and Tolerance Technique Against Attacks and Faults on Leader-Following Multi-USVs

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    This study explores the leader-following consensus tracking control issue of multiple unmanned surface vehicles (multi-USVs) in the presence of malicious connectivity-mixed attacks in the cyber layer, and concurrent output channel noises, sensor/actuator faults, and wave-induced disturbances in the physical layer. Sensor/actuator faults are initially modeled with unified incipient and abrupt features. Additionally, connectivity-mixed attacks are depicted using connectivity-paralyzed and connectivity-maintained topologies through nonoverlapping and switching iterations. The standardization and observer design in multi-USVs are incorporated to decouple the augmented dynamics and estimate unknown state, fault, and noise observations, and then a defense and fault-tolerant consensus tracking control approach is designed to accomplish the robustness to disturbances/noises, resilience to attacks, and tolerance to faults, simultaneously. The criteria for achieving leader-following exponential consensus tracking of multi-USVs with cyber-physical threats can be determined based on activation rate and attack frequency indicators. Comparative simulations outline the effectiveness and economy of the proposed defense and tolerance technique against sensor/actuator faults and cyber-attacks on multi-USVs

    Ordering dynamics in the voter model with aging

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    The voter model with memory-dependent dynamics is theoretically and numerically studied at the mean-field level. The `internal age', or time an individual spends holding the same state, is added to the set of binary states of the population, such that the probability of changing state (or activation probability pip_i) depends on this age. A closed set of integro-differential equations describing the time evolution of the fraction of individuals with a given state and age is derived, and from it analytical results are obtained characterizing the behavior of the system close to the absorbing states. In general, different age-dependent activation probabilities have different effects on the dynamics. When the activation probability pip_i is an increasing function of the age ii, the system reaches a steady state with coexistence of opinions. In the case of aging, with pip_i being a decreasing function, either the system reaches consensus or it gets trapped in a frozen state, depending on the value of p∞p_\infty (zero or not) and the velocity of pip_i approaching p∞p_\infty. Moreover, when the system reaches consensus, the time ordering of the system can be exponential (p∞>0p_\infty>0) or power-law like (p∞=0p_\infty=0). Exact conditions for having one or another behavior, together with the equations and explicit expressions for the exponents, are provided

    Consensus-based control for a network of diffusion PDEs with boundary local interaction

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    In this paper the problem of driving the state of a network of identical agents, modeled by boundary-controlled heat equations, towards a common steady-state profile is addressed. Decentralized consensus protocols are proposed to address two distinct problems. The first problem is that of steering the states of all agents towards the same constant steady-state profile which corresponds to the spatial average of the agents initial condition. A linear local interaction rule addressing this requirement is given. The second problem deals with the case where the controlled boundaries of the agents dynamics are corrupted by additive persistent disturbances. To achieve synchronization between agents, while completely rejecting the effect of the boundary disturbances, a nonlinear sliding-mode based consensus protocol is proposed. Performance of the proposed local interaction rules are analyzed by applying a Lyapunov-based approach. Simulation results are presented to support the effectiveness of the proposed algorithms

    Network Inference from Consensus Dynamics

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    We consider the problem of identifying the topology of a weighted, undirected network G\mathcal G from observing snapshots of multiple independent consensus dynamics. Specifically, we observe the opinion profiles of a group of agents for a set of MM independent topics and our goal is to recover the precise relationships between the agents, as specified by the unknown network G\mathcal G. In order to overcome the under-determinacy of the problem at hand, we leverage concepts from spectral graph theory and convex optimization to unveil the underlying network structure. More precisely, we formulate the network inference problem as a convex optimization that seeks to endow the network with certain desired properties -- such as sparsity -- while being consistent with the spectral information extracted from the observed opinions. This is complemented with theoretical results proving consistency as the number MM of topics grows large. We further illustrate our method by numerical experiments, which showcase the effectiveness of the technique in recovering synthetic and real-world networks.Comment: Will be presented at the 2017 IEEE Conference on Decision and Control (CDC

    Interacting Agents and Continuous Opinions Dynamics

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    We present a model of opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold. High thresholds yield convergence of opinions towards an average opinion, whereas low thresholds result in several opinion clusters. The model is further generalised to network interactions, threshold heterogeneity, adaptive thresholds and binary strings of opinions.Comment: 21 pages, 13 figures. http://www.lps.ens.fr/~weisbuch/contopidyn/contopidyn.htm

    Time-Varying Beta: A Boundedly Rational Equilibrium Approach

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    By taking into account conditional expectations and the dependence of the systematic risk of asset returns on micro- and macro-economic factors, the conditional CAPM with time-varying betas displays superiority in explaining the cross-section of returns and anomalies in a number of empirical studies. Most of the literature on time-varying beta is motivated by econometric estimation rather than explicit modelling of the stochastic behaviour of betas through agents' behaviour. Within the mean-variance framework of repeated one-period optimisation, we set up a boundedly rational dynamic equilibrium model of a financial market with heterogeneous agents and obtain an explicit dynamic CAPM relation between the expectede quilibrium returns and time-varying betas. By incorporating the three most popular types of investors, fundamentalists, chartists and noise traders, into the model, we show that, independent of the fundamentals, there is a systematic change in the market portfolio, risk-return relationships, and time varying betas when investors change their behaviour, such as the chartists acting as momentum traders. In particular, we demonstrate the stochastic nature of time-varying betas and show that the commonly used rolling window estimates of time-varying betas may not be consistent with the ex-ante betas implied by the equilibrium model. The results provide a number of insights into an understanding o ftime-varying beta.equilibrium asset prices; CAPM; time-varying betas, heterogeneous expectations
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